1. From information to data, and back again
Laine Ruus
University of Toronto.Data Library Service

2. Overview The DIKW model and where libraries fit
Where data have been (and are still)
Data and the reference librarian

3. Wisdom Knowledge Information Data
The DIKW model
Wisdom Knowledge Information Data

4. Library systems are…
Set up, resourced and trained to locate information that exists
Not set up, resourced or trained to generate information that does not yet exist

5. Data have been around for a long time
Population census,since s
Public opinion polls, since early 1900s
Social surveys since early 1900s

6. …and they have been hiding in…
Early data archives (1940s and on) in local academically-based survey institutions and data archives
Later, national data archives, esp in Europe
1957 Lucci et al report, suggested libraries as appropriate organizations in which to situate data services
At UBC, Jean LaPonce, 1972, one of first with Library involvement, like Columbia/EDS,
in USA, ca 42% of academic services in libraries

7. North American model
Puts user services close to users, but not close enough; data services usually a discrete entity
Possibility of a quantitative answer should be part of every reference interview
Now possible – convergence of Inet, DDI metadata standard, and rise of 3rd generation interfaces to microdata: SDA, Nesstar, VDC

8. Requires a new set of skills
The hardware and software are now available to support generation of descriptive and inferential statistics from raw microdata at the reference desk
Requires:
Numeracy: how to interpret statistics
Knowledge how and by whom data are collected
Knowledge how data become statistics

9. Time to take up Lucci et al challenge
Only data management needs to be a discrete entity
Quantitative reference services should be part of every reference tool basket